List roles in CloudStack
AI agents call list_roles to retrieve information from CloudStack MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns role information from CloudStack without creating, modifying, or deleting any resources. It is a straightforward read operation that poses minimal risk even if misused by an AI agent, as it only reveals existing role definitions.
From the tool's definition Tool name is 'list_roles' and description states 'List roles in CloudStack' — a retrieval operation with no modification or side effects.
Attacks that exploit this kind of access
List roles in CloudStack. It is categorised as a Read tool in the CloudStack MCP Server MCP Server, which means it retrieves data without modifying state.
Register the CloudStack MCP Server MCP server in PolicyLayer and add a rule for list_roles: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches CloudStack MCP Server. Nothing to install.
list_roles is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_roles rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for list_roles. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
list_roles is provided by the CloudStack MCP Server MCP server (mozg31337/cloudstack-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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